基于运动序列分割的运动捕获数据关键帧提取

Extraction of Keyframe from Motion Capture Data Based on Motion Sequence Segmentation

采用线性时不变系统把高维运动数据映射到低维状态空间;在低维状态空间中,定义了姿态之间的相似性度量;并采用误差平方和准则对时序的低维数据点集进行运动分割,分割点上的运动姿态被定义为关键帧.实验结果表明:该算法能够较好地提取出运动序列中的关键帧,并且这些关键帧能够很好地概括原始运动序列的内容.

Linear time-invariant system is used to derive an explicit mapping between the high- dimensional motion capture data and the low-dimensional state variables. A similarity metric is defined to measure the difference between different poses in the low-dimensional state space, and then the method of mean squared error is employed to divide the motion sequence into a sequence of concatenated segments. The poses at these segmentation points are then defined as keyframes. Experimental results show that the extracted keyframes by our method can give a good visual summarization of the original motion sequence.